Big data and AI partnership: GenAI solutions provider Shorthills AI has partnered with Databricks for combining data and analytics with artificial intelligence, the companies said on Wednesday.

As part of the partnership, Shorthills AI will leverage its expertise in AI while Databricks will gauge the utility of its Data Intelligence Platform for bridging gaps in collaboration, analytical workflows and Big Data infrastructure.

Shorthills AI is into business transformation through AI, making data actionable and driving digital innovation.

The Databricks Data Intelligence Platform provides an open, unified foundation for major data workloads and use cases, which include ETL, data warehousing and generative AI as part of a single platform for collaboration. 

The partnership will enable enterprise organisations to realise enhanced data analytics, improved operational efficiency, and accelerated time-to-insight through integrated AI and machine learning capabilities.

Paramdeep Singh, co-founder of Shorthills AI said the partnership is setting a new standard for what enterprises can achieve with their data, driving growth and innovation in an increasingly competitive landscape.

As per a report by Market Research Future, the GenAI market is estimated to reach a compound annual growth rate (CAGR) of over 30 per cent from 2022 to 2027.

In terms of data, it is predicted that the global datasphere is projected to reach an astounding 175 zettabytes by 2025, according to a Statista analysis.

The combination of Big Data and AI plays a pivotal role in healthcare via  electronic health records (EHRs) and medical imaging, which generate vast data for disease diagnosis, predicting patient outcomes and recommending personalised treatment plans. 

A similar use case is visible in cybersecurity, wherein  identifying unusual patterns or outliers in large datasets is crucial.

Converging Big Data and AI aids manufacturing by implementing Industry 4.0 initiatives, wherein smart factories are leveraging IoT sensors to collect vast data on machinery and production processes.

This also has applications in urban planning and smart cities.